






import os

import numpy
import onnx

def        UpperCAmelCase__		(						lowerCamelCase_       :       List[str]   ,  lowerCamelCase_       :       List[Any]				):
			__a						:  Union[str, Any]									=     a.name
			__a						:  Dict									=     b.name

			__a						:  Dict									=     ''
			__a						:  Tuple									=     ''

			__a						:  Optional[int]									=     a == b

			__a						:  Dict									=     name_a
			__a						:  Tuple									=     name_b

			return res

def        UpperCAmelCase__		(						lowerCamelCase_       :       List[str]   ,  lowerCamelCase_       :       Optional[int]   ,  lowerCamelCase_       :       Tuple				):
			for i, input_name in enumerate(node_proto.input				):
						if input_name == name:
									node_proto.input.insert(lowerCamelCase_   ,  lowerCamelCase_				)
									node_proto.input.pop(i + 1				)

			if node_proto.op_type == "If":
						_graph_replace_input_with(node_proto.attribute[0].g   ,  lowerCamelCase_   ,  lowerCamelCase_				)
						_graph_replace_input_with(node_proto.attribute[1].g   ,  lowerCamelCase_   ,  lowerCamelCase_				)
			if node_proto.op_type == "Loop":
						_graph_replace_input_with(node_proto.attribute[0].g   ,  lowerCamelCase_   ,  lowerCamelCase_				)

def        UpperCAmelCase__		(						lowerCamelCase_       :       Any   ,  lowerCamelCase_       :       int   ,  lowerCamelCase_       :       Optional[int]				):
			for n in graph_proto.node:
						_node_replace_input_with(lowerCamelCase_   ,  lowerCamelCase_   ,  lowerCamelCase_				)

def        UpperCAmelCase__		(						lowerCamelCase_       :       List[str]   ,  lowerCamelCase_       :       List[str]   ,  lowerCamelCase_       :       List[str]				):
			__a						:  Any									=     list(model.graph.initializer				)
			__a						:  Optional[Any]									=     list(model_without_ext.graph.initializer				)
			for i, ref_i in ind_to_replace:
						assert inits_with_data[i].name == inits[i].name
						assert inits_with_data[ref_i].name == inits[ref_i].name
						assert i > ref_i

						__a						:  Tuple									=     inits[i].name
						__a						:  str									=     inits[ref_i].name

						model_without_ext.graph.initializer.remove(inits[i]				)

						# for n in model.graph.node:
						_graph_replace_input_with(model_without_ext.graph   ,  lowerCamelCase_   ,  lowerCamelCase_				)

def        UpperCAmelCase__		(						lowerCamelCase_       :       List[Any]				):
			__a						:  int									=     os.path.dirname(lowerCamelCase_				)
			__a						:  Any									=     os.path.basename(lowerCamelCase_				)

			__a						:  Any									=     onnx.load(os.path.join(lowerCamelCase_   ,  lowerCamelCase_				)				)

			__a						:  str									=     list(model.graph.initializer				)

			__a						:  Union[str, Any]									=     set()
			__a						:  Union[str, Any]									=     {}
			__a						:  Optional[int]									=     []

			__a						:  Dict									=     0

			for i in range(len(lowerCamelCase_				)				):
						if i in dup_set:
									continue

						for j in range(i + 1   ,  len(lowerCamelCase_				)				):
									if j in dup_set:
												continue
									if _is_equal_tensor_proto(inits[i]   ,  inits[j]				):
												dup_set.add(lowerCamelCase_				)
												dup_set.add(lowerCamelCase_				)

												__a						:  Union[str, Any]									=     inits[j].data_type
												__a						:  Tuple									=     numpy.prod(inits[j].dims				)
												if dtype == 1:
															mem_size *= 4
												elif dtype == 6:
															mem_size *= 4
												elif dtype == 7 or dtype == 1_1:
															mem_size *= 8
												else:
															print('unexpected data type: '   ,  lowerCamelCase_				)
												total_reduced_size += mem_size

												__a						:  Dict									=     inits[i].name
												__a						:  Any									=     inits[j].name

												if name_i in dup_map:
															dup_map[name_i].append(lowerCamelCase_				)
												else:
															__a						:  List[Any]									=     [name_j]
												ind_to_replace.append((j, i)				)

			print('total reduced size: '   ,  total_reduced_size / 1_0_2_4 / 1_0_2_4 / 1_0_2_4   ,  'GB'				)

			__a						:  Optional[Any]									=     sorted(lowerCamelCase_				)
			_remove_dup_initializers_from_model(lowerCamelCase_   ,  lowerCamelCase_   ,  lowerCamelCase_				)

			__a						:  Tuple									=     'optimized_' + model_file_name
			__a						:  Tuple									=     os.path.join(lowerCamelCase_   ,  lowerCamelCase_				)
			onnx.save(lowerCamelCase_   ,  lowerCamelCase_				)

			return new_model












"""simple docstring"""





def      UpperCAmelCase__				(    SCREAMING_SNAKE_CASE	:		int				,		SCREAMING_SNAKE_CASE	:		int     ):







      '''simple docstring'''




      if a < 0 or b < 0:
            raise ValueError("""the value of both inputs must be positive"""     )
      lowerCAmelCase    		=			str(bin(SCREAMING_SNAKE_CASE     )     )[2:]  # remove the leading "0b"
      lowerCAmelCase    		=			str(bin(SCREAMING_SNAKE_CASE     )     )[2:]
      lowerCAmelCase    		=			max(len(SCREAMING_SNAKE_CASE     )				,		len(SCREAMING_SNAKE_CASE     )     )
      return "0b" + "".join(
          str(int("""1""" in (char_a, char_b)     )     )
          for char_a, char_b in zip(a_binary.zfill(SCREAMING_SNAKE_CASE     )				,		b_binary.zfill(SCREAMING_SNAKE_CASE     )     )     )


if __name__ == "__main__":
       import doctest

       doctest.testmod()






